class_docstr: Determines the mean number of characters per word.
  
  Description:
      Given list of strings, determine the mean number of
      characters per word in each string. A word is defined as
      a series of any characters not separated by white space.
      Punctuation is removed before counting. If a string
      is empty or `NaN`, return `NaN`.
  
  Examples:
      >>> x = ['This is a test file', 'This is second line', 'third line $1,000']
      >>> mean_characters_per_word = MeanCharactersPerWord()
      >>> mean_characters_per_word(x).tolist()
      [3.0, 4.0, 5.0]
code: def get_function(self):
      def mean_characters_per_word(series):
          return series.apply(_mean_characters_per_word)
  
      return mean_characters_per_word
  
file_path: featuretools/featuretools/primitives/standard/transform/natural_language/mean_characters_per_word.py
imports: import re
  import numpy
  import pandas
  from woodwork.column_schema import ColumnSchema
  from woodwork.logical_types import Double, NaturalLanguage
  from featuretools.primitives.base import TransformPrimitive
label_desc: Use image node_id 1 for calling the MeanCharactersPerWord obj's underlying member method code with example usage: obj.get_function() and returns: mean_characters_per_word, series